Phenotypiccelltransitionsareintegraltotissuedevelopment,regeneration,andhomeostasis, whereasinglepotentcelltypecangiverisetomorethanonefunctionallydistinctcelltype.To better understand the dynamics of cell fate decisions, a lineage topology, from common progenitortoeachdifferentiatedcellstate,mustbeknown.Whilesignalingprofilesofcellular end states, stem and differentiated states, are generally well characterized, the signaling dynamics along each trajectory and at branch points, splits in a common lineage, are less defined. Recent computational approaches have focused on defining stemdifferentiated cell transitions from single cell data. Defining the temporal progression of cell transitions is challengingduetothecontinuumofcellstatesthatexistbetweenstablestates.Whileprevious efforts have successfully mapped linear differentiation lineages, no approach exists that can map branched differentiation lineages with statistically testable results. Our method borrows concepts from graph theory, where a spanning tree is constructed from a densitydependent down sampled set of datapoints. Lineage branches and cellular end states (stem cells and differentiatedcelltypes)areidentifiedbycloseness,agraphattribute.Theresultingtransition mapsarestatisticallyscoredbothglobally,ontheoveralltopology,andlocally,oneachbranch point, using a modified rootmean squared deviation algorithm. A final transitional map comprisesasetoftopscoringlineageswhichcanbevalidatedagainstthespatialtemporalcell progression of the crypt. Our hypothesis is that a cell makes its fate decision based upon a probabilisticdistributionconditionedonitscurrentstate,itsage,andthestateofitssurrounding neighbors.Fromhyperplexedimagingtechnology,wewillmodelprobabilisticcellfatedecisions usingaBayesianframeworktoconstructtopologiesofsignalingdependencies.Themammalian intestinalepitheliumisourmodelsystem,whereitsshortturnovertimenecessitatescontinuous regenerationanddifferentiationofepithelialcells.Onceestablished,ourmodelwillprovidean uniqueinsightintotheeffectofdiseaseonstemdifferentiatedcelltransitions,pavingthewayfor newsystemsbasedtherapeutics.